1 citations · 1 across the 9 of their papers we have counts for
11 papers · 1 filter
Predicting Human Visual Attention on Words in Source Code
Chia-Yi Su, Collin McMillan
This paper presents a computational model to predict human visual attention over words in software source code. The visual attention of software engineers when reading source code…
CMind: An AI Agent for Localizing C Memory Bugs
Chia-Yi Su, Collin McMillan
This demonstration paper presents CMind, an artificial intelligence agent for localizing C memory bugs. The novel aspect to CMind is that it follows steps that we observed human pr…
AI-Mediated Code Comment Improvement
Maria Dhakal, Chia-Yi Su, Robert Wallace +5
This paper describes an approach to improve code comments along different quality axes by rewriting those comments with customized Artificial Intelligence (AI)-based tools. We cond…
Do Code LLMs Do Static Analysis?
Chia-Yi Su, Collin McMillan
This paper investigates code LLMs' capability of static analysis during code intelligence tasks such as code summarization and generation. Code LLMs are now household names for the…
Which Code Statements Implement Privacy Behaviors in Android Applications?
Chia-Yi Su, Aakash Bansal, Vijayanta Jain +3
A "privacy behavior" in software is an action where the software uses personal information for a service or a feature, such as a website using location to provide content relevant…
Context-aware Code Summary Generation
Chia-Yi Su, Aakash Bansal, Yu Huang +2
Code summary generation is the task of writing natural language descriptions of a section of source code. Recent advances in Large Language Models (LLMs) and other AI-based technol…
Revisiting File Context for Source Code Summarization
Aakash Bansal, Chia-Yi Su, Collin McMillan
Source code summarization is the task of writing natural language descriptions of source code. A typical use case is generating short summaries of subroutines for use in API docume…
Modeling Programmer Attention as Scanpath Prediction
Aakash Bansal, Chia-Yi Su, Zachary Karas +4
This paper launches a new effort at modeling programmer attention by predicting eye movement scanpaths. Programmer attention refers to what information people intake when performin…
Distilled GPT for Source Code Summarization
Chia-Yi Su, Collin McMillan
A code summary is a brief natural language description of source code. Summaries are usually only a single sentence long, and yet form the backbone of developer documentation. A sh…
Semantic Similarity Loss for Neural Source Code Summarization
Chia-Yi Su, Collin McMillan
This paper presents a procedure for and evaluation of using a semantic similarity metric as a loss function for neural source code summarization. Code summarization is the task of…
A Language Model of Java Methods with Train/Test Deduplication
Chia-Yi Su, Aakash Bansal, Vijayanta Jain +2
This tool demonstration presents a research toolkit for a language model of Java source code. The target audience includes researchers studying problems at the granularity level of…